Location marteau piqueur à 78340 Clayes-sous-bois

1. 0.0002

   SELECT cate_title_slug FROM category WHERE fami_id IN (3,5) AND cate_title_slug<>'' AND cate_title_slug IS NOT NULL

2. 0.0001

   SELECT cate_id FROM category WHERE fami_id='5' AND cate_title_slug='materiel-bricolage'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=87

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='78'

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='78340' AND ville_nom like '%clayes%sous%bois%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0005

   SELECT DISTINCT ssrubr_slug FROM ssrubr WHERE ssrubr_visu=1 AND fami_id IN (3,5) AND ssrubr_slug IS NOT NULL AND ssrubr_slug<>''

7. 0.0002

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%marteau%piqueur%' OR ssrubr_title like '%marteau%piqueur%' OR ssrubr_slug like '%marteau%piqueur%') AND cate_id='87' ORDER BY ssrubr_id LIMIT 0,1

8. 0.0001

   SHOW TABLES LIKE 'pays'

9. 0.0002

   SHOW COLUMNS FROM pays LIKE 'pays_tel_%'

10. 0.0003

    SELECT pays_code, pays_nom, pays_actif, pays_NDD, pays_drapeau, pays_lang, pays_tel, pays_nb_annonces, pays_tel_masque, pays_tel_max, pays_tel_fmt_paires, pays_tel_mode FROM pays ORDER BY pays_nom ASC

11. 0.0001

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='78340'

12. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((48.8167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.98333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.636835678816 AND ville_latitude_deg<48.996564321184 AND ville_longitude_deg>1.7101746819952 AND ville_longitude_deg<2.2564853180048 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='marteau piqueur'

14. 0.0003

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='87'AND MATCH (wish_title,wish_desc) AGAINST ('+marteau piqueur*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '78340%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=87

16. 0.0004

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='marteau piqueur' OR ssrubr_slug='marteau-piqueur' OR (ssrubr_title like '%marteau piqueur%')) AND cate_id='87' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='marteau-piqueur' AND cate_id='87'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78340'

19. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((48.8167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.98333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.636835678816 AND ville_latitude_deg<48.996564321184 AND ville_longitude_deg>1.7101746819952 AND ville_longitude_deg<2.2564853180048 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0064

    SELECT ville_cp, ROUND((((acos(sin((48.8167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.98333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.367039197041 AND ville_latitude_deg<49.266360802959 AND ville_longitude_deg>1.3004358163378 AND ville_longitude_deg<2.6662241836622 HAVING distance <= 50 ORDER BY distance ASC

21. 0.1005

    SELECT wish.*, ui.util_photo, ui.util_prenom, ui.util_nom, ui.stripe_account_id, ui.util_verify, ville_cp,ville_nom,ville_latitude_deg,ville_longitude_deg, ROUND((((acos(sin((48.8167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.98333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM wish LEFT JOIN util_info ui ON wish.util_id=ui.util_id LEFT JOIN villes v ON wish.wish_cp=v.ville_cp WHERE wish_id IS NOT NULL AND fami_id='5' AND cate_id='87' AND MATCH (wish_desc) AGAINST ('(+marteau +piqueur*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (78340,78340,78370,78450,78390,78450,78190,78860,78990,78330,78590,78810,78640,78850,78640,78210,78180,78810,78760,78590,78640,78310,78320,78870,78620,78121,78280,78640,78960,78310,78160,78650,78490,78320,78240,78470,78112,78150,78240,78750,78150,78690,78490,78490,78470,78490,78114,78630,78650,78000,78430,78124,78320,78100,78580,78580,78560,78117,78380,78290,78350,78530,78770,78720,78230,78124,78117,78690,78170,78490,78490,78720,78490,78770,78490,78110,78630,78490,78220,78300,78460,78770,92420,92430,78400,78770,78770,78350,78140,78580,91190,78720,78670,78670,92380,78470,78610,78460,78955,92410,78580,78920,91470,91190,78770,92310,78940,92370,78126,78610,78490,91400,78360,78540,78720,78600,78130,78890,92210,78770,92500,78410,78260,91470,78610,78125,92000,78580,78420,78910,91430,78940,78410,78410,91940,91190,78480,78510,91570,78910,91440,78410,78570,92360,92190,92800,92150,91470,78600,78680,78410,91400,78800,78930,78610,91430,78570,91400,92100,78490,91470) AND type_id=1 GROUP BY wish_id

22. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 26878 AND W.type_id = 1) OR (W.util_id <> 26878 AND W.type_id = 2)) AND (M.post_util_id = 26878 OR M.dest_util_id = 26878) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

23. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=26878 AND note_visu IN (1,3,4)

24. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 107685 AND W.type_id = 1) OR (W.util_id <> 107685 AND W.type_id = 2)) AND (M.post_util_id = 107685 OR M.dest_util_id = 107685) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

25. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=107685 AND note_visu IN (1,3,4)

26. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 132543 AND W.type_id = 1) OR (W.util_id <> 132543 AND W.type_id = 2)) AND (M.post_util_id = 132543 OR M.dest_util_id = 132543) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

27. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=132543 AND note_visu IN (1,3,4)

28. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 115331 AND W.type_id = 1) OR (W.util_id <> 115331 AND W.type_id = 2)) AND (M.post_util_id = 115331 OR M.dest_util_id = 115331) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

29. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=115331 AND note_visu IN (1,3,4)

30. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 202102 AND W.type_id = 1) OR (W.util_id <> 202102 AND W.type_id = 2)) AND (M.post_util_id = 202102 OR M.dest_util_id = 202102) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

31. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=202102 AND note_visu IN (1,3,4)

32. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 217518 AND W.type_id = 1) OR (W.util_id <> 217518 AND W.type_id = 2)) AND (M.post_util_id = 217518 OR M.dest_util_id = 217518) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

33. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=217518 AND note_visu IN (1,3,4)

34. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 172204 AND W.type_id = 1) OR (W.util_id <> 172204 AND W.type_id = 2)) AND (M.post_util_id = 172204 OR M.dest_util_id = 172204) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

35. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=172204 AND note_visu IN (1,3,4)

36. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 216224 AND W.type_id = 1) OR (W.util_id <> 216224 AND W.type_id = 2)) AND (M.post_util_id = 216224 OR M.dest_util_id = 216224) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

37. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=216224 AND note_visu IN (1,3,4)

38. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 320176 AND W.type_id = 1) OR (W.util_id <> 320176 AND W.type_id = 2)) AND (M.post_util_id = 320176 OR M.dest_util_id = 320176) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

39. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=320176 AND note_visu IN (1,3,4)

40. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 390960 AND W.type_id = 1) OR (W.util_id <> 390960 AND W.type_id = 2)) AND (M.post_util_id = 390960 OR M.dest_util_id = 390960) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

41. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=390960 AND note_visu IN (1,3,4)

42. 0.0005

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 311956 AND W.type_id = 1) OR (W.util_id <> 311956 AND W.type_id = 2)) AND (M.post_util_id = 311956 OR M.dest_util_id = 311956) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

43. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=311956 AND note_visu IN (1,3,4)

44. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78340'

45. 0.0017

    SELECT ville_cp, ROUND((((acos(sin((48.8167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.98333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.636835678816 AND ville_latitude_deg<48.996564321184 AND ville_longitude_deg>1.7101746819952 AND ville_longitude_deg<2.2564853180048 HAVING distance <= 20 ORDER BY distance ASC

46. 0.0062

    SELECT ville_cp, ROUND((((acos(sin((48.8167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.98333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.367039197041 AND ville_latitude_deg<49.266360802959 AND ville_longitude_deg>1.3004358163378 AND ville_longitude_deg<2.6662241836622 HAVING distance <= 50 ORDER BY distance ASC

47. 0.0001

    SELECT ssr.ssrubr_id, ssr.ssrubr_slug, ssr.ssrubr_mail, ssr.ssrubr_mail_bis, ssr.ssrubr_keywords, ssr.ssrubr_bt2, ssr.ssrubr_photo, c.cate_title_slug, f.fami_url FROM ssrubr ssr, category c, family f WHERE ssr.cate_id=c.cate_id AND c.fami_id=f.fami_id AND ssr.ssrubr_id IN (29,58,50)

48. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (26878,390960,217518,311956,172204,115331,202102,216224,320176,107685,132543)

49. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (26878,390960,217518,311956,172204,115331,202102,216224,320176,107685,132543)

50. 0.0003

    SELECT ssrubr_id, ssrubr_title, ssrubr_slug, ssrubr_photo, cate_title_slug FROM ssrubr ss, category c WHERE ss.cate_id=c.cate_id AND ssrubr_visu=1 AND ss.cate_id=87 AND ss.fami_id=5 ORDER BY ssrubr_order LIMIT 6,100

51. 0.0002

    SELECT ss.fami_id, fami_url, ss.cate_id, cate_title_slug, keywords_title FROM `ssrubr_keywords` sk, ssrubr ss, category c, family f WHERE sk.ssrubr_id=ss.ssrubr_id AND ss.cate_id=c.cate_id AND c.fami_id=f.fami_id AND (ssrubr_slug='marteau piqueur' OR ssrubr_slug like '%marteau piqueur%' OR MATCH (ssrubr_slug) AGAINST ('(+marteau +piqueur)')) AND sk.ssrubr_id='58' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

52. 0.0003

    SELECT ss.ssrubr_id, ss.ssrubr_slug, ss.ssrubr_title, ss.ssrubr_keywords, ss.ssrubr_mail, c.cate_title_slug FROM ssrubr ss INNER JOIN category c ON ss.cate_id = c.cate_id WHERE ss.ssrubr_visu = 1 AND ss.fami_id = 5 AND ss.cate_id = 87 AND ss.ssrubr_id <> 58 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

53. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='58' AND actu_niveau=0 ORDER BY actu_ordre DESC

54. 0.0001

    SELECT fami_id as id, fami_title as title, fami_tutotitle, fami_tutodesc, fami_buttontitle, fami_url as slug FROM `family`

55. 0.0001

    SELECT cate_id as id, cate_title as title, cate_title_slug as slug, fami_id FROM `category` WHERE cate_visu=1 AND fami_id='5' AND cate_cate_id IS NULL ORDER BY cate_order ASC

56. 0.0003

    SELECT ssrubr_id AS id, ssrubr_title as title, ssrubr_slug as slug, ssrubr_photo, cate_id, fami_id FROM ssrubr WHERE ssrubr_visu=1 AND cate_id IN (87) ORDER BY ssrubr_order ASC

57. 0.0009

    SELECT AVG(note) as note_moy FROM note WHERE note_visu IN (1,2,3,4) AND post_util_id<>7

58. 0.0218

    SELECT COUNT(*) AS nbavis FROM note n INNER JOIN util_info dest ON n.dest_util_id=dest.util_id INNER JOIN util_info post ON n.post_util_id=post.util_id INNER JOIN wish w ON n.wish_id=w.wish_id WHERE n.note_visu IN (1,2,3,4) AND n.post_util_id<>'7'

59. 0.0194

    SELECT count(*) as nbwish FROM wish WHERE wish_visu IN (1,6,10)

59 requetes sql en 0.1691